Eric Luellen

Technology Executive, Information Technology and Services

Hi, I'm Eric Luellen, a data science strategist, technologist, product innovator, and serial entrepreneur.

Eric Luellen's Bio:

Eric Luellen is a technology executive and data science leader who works with e-commerce, education tech, financial tech, and public health organizations to maximize insights and competitive advantages with artificial intelligence (AI) and machine learning (ML). Eric believes that data science empowers organizations to achieve unprecedented results, for less cost, and the highest quality service and value. In 24 years, Eric Luellen has founded and grown three technology companies and led technology initiatives in data science and software development, supporting global organizations, and worked or traveled in 34 countries. ● 24 years experience leading enterprise software development in analytics, AI & machine learning Domain expertise in disease diagnostics, management, genetics, and therapeutics ● Led up to 130 personnel and $6 million budgets ● Two advanced degrees plus 36 credit hours in biomedical sciences + 10 advanced certificates (Harvard, Caltech, MIT, Wharton) ● A thought leader with over 50,000 readers in AI Published ML research in leading journals and referee for leading journals ● Won global awards applying AI to healthcare ● Extensive experience in business with novel use cases applying AI/ML to digital health problems. Representative projects include: ● 40 digital diagnostic & digital therapeutic algorithms for asthma, breast cancer, CHD, COPD, depression, diabetes, emphysema, gout, heart failure, high cholesterol, hyper/hypotension, insomnia, liver disease, osteoporosis, & prostate cancer ● Digital therapeutic for arthritis and inflammation for US Air Force Research Laboratory with 80.6% accuracy ● AI Digital health monitoring (Medication adherence & pharmacovigilance) - Led design and development of rules-based AI system for real-time monitoring and notification for predictive medicine - Global finalist for C3 Prize at Stanford MedX and World Technology Award in health and medicine. ● Trafficking Prediction - Developed an algorithm to predict whether or not a person was being trafficked using a comparative ensemble of decision trees, random forest, extreme gradient boosting, logistic regression, and neural networks in R. ● Trafficking Locations - Developed an algorithm to predict which borders had the highest prevalence of trafficking to prioritize border monitoring using Poisson and stepwise regression or ordinal data. ● Fundraising - Developed algorithms to segment donors by behavior using self-organizing maps and predict attrition using random forests and extreme gradient boosting in R. ● Machine learning educational tech - Led the design, development, and release of algorithms to optimize financial aid, and predict student attrition and tuition defaults, and optimize COVID-19 appeals using ensembles of ML algorithms in R (automated ML) ● AI Financial tech - Led the design and development of AI rules-based system for financial planning -- retirement plan options, etc. ● Talent ID - Developed an algorithm to predict the highest performers with 77-97% accuracy using best subset multiple regression. Eric Luellen holds a Master of Public Health (MPH) degree focusing in biostatistics from the University of Massachusetts Amherst, a Master of Science degree in informatics from Northwestern University, 10 advanced certificates in business, finance, negotiations, and technology from Caltech, Columbia University, Harvard Law School's Program on Negotiations, MIT's Sloan School of Management, and the University of Pennsylvania's Wharton School of Business, plus 36 credit hours in genomics, virology, infectious disease, epidemiology, psychology, and environmental health from Harvard University. Eric Luellen holds a Bachelor of Arts degree in liberal arts, concentrating in economics, from American University. Eric Luellen has been invited presenter or headliner at the World Congress of Bioethics (2020), AI World - Boston (2018), Korean Startup Festival - Seoul (2017), SLUSH Shanghai (2017), StartupBootCamp, China (2017), and Health 2.0 - Seoul (2016). In February 2020, Eric's first data-science textbook -- Beating Amazon: The Machine Learning Guide to Win the E-Commerce War was published by Social Justice Press (www.BeatingAmazon.net). Eric Luellen is a former officer in Young Presidents' Organization (YPO) and the Society for Information Management (SIM). Eric joined the Forbes Technology Council in 2020 and has an online readership in excess of 40,000. Eric is an Eagle Scout and holds a black belt in Isshinryu karate.

Eric Luellen's Experience:

  • Co-founder & Chief Data Scientist at Bioinformatix LLC

    August 2015 - Present | Boston, Massachusetts

    Lead strategy, design & development of next-generation analytic & machine-learning platforms to solve biomedical problems, focused in Software as a Medical Device (SaMD) and public health; accomplished projects include leading all phases from ideation through the delivery of: ● 40 digital diagnostic & digital therapeutic algorithms for asthma, breast cancer, CHD, COPD, depression, diabetes, emphysema, gout, heart failure, high cholesterol, hyper/hypotension, insomnia, liver disease, osteoporosis, & prostate cancer ● Digital therapeutic for arthritis and inflammation for US Air Force Research Laboratory with 80.6% accuracy ● AI Digital health monitoring (Medication adherence & pharmacovigilance) - Led design and development of rules-based AI system for real-time monitoring and notification for predictive medicine - Global finalist for C3 Prize at Stanford MedX and World Technology Award in health and medicine

  • Chief Data Scientist at Global Social Mission

    November 2019 - June 2020

    Led data science strategies and implementation across projects for a global charity focused on combatting human trafficking, family homes and schools for orphans, and COVID-19 relief efforts across 14 countries (part-time after hours). Representative projects included: ● Talent ID - Developed an algorithm to predict the highest performers with 77-97% accuracy using best subset multiple regression ● Nutrition - Developed analysis to identify and plot malnourished children by percentage BMI. ● Trafficking Prevalence - Co-developed research study to measure the prevalence of human trafficking. ● Trafficking Prediction - Developed an algorithm to predict whether or not a person was being trafficked using a comparative ensemble of decision trees, random forest, extreme gradient boosting, logistic regression, and neural networks in R. ● Trafficking Locations - Developed an algorithm to predict which borders had the highest prevalence of trafficking to prioritize border monitoring using Poisson and stepwise regression or ordinal data. ● Fundraising - Developed algorithms to segment donors by behavior using self-organizing maps and predict attrition using random forests and extreme gradient boosting in R.

  • Senior Advisor at Georgetown Strategies

    January 2014 - February 2017 | Boston

    • Led technology strategy and development projects as interim CTO for $9M software company conducting B2B2C clinical informatics and predictive analytics for global pharmaceutical companies • Led preparations for successful ISO & HIPAA audits  Trained staff on translating user needs into actionable requirements for software engineering  Led development of novel analytics approaches and wrote proposal for Defense Advanced Research Projects Agency (DARPA) in probabilistic modeling

  • Founder & Chief Data Scientist at iDok

    July 2008 - November 2014

    • Led product strategy, design & development of a Bayesian decision-support system from conception through testing on Beta version with 2,500 diseases and 4,000 symptoms and risks for over 50 million combinations • Led the design & development of production system for 13,800 diseases and 4,000 symptoms and risk factors including manually building knowledge base, developing algorithms, and data extract-transform-load (ETL)

Eric Luellen's Education:

  • UMASSS-Amherst

    2018 – 2020
    Master of Public Health (MPH)
    Concentration: Practice Management & Biostatistics
    Activities: GPA 3.9

  • Northwestern University

    2016 – 2017
    Master of Science
    Concentration: Health Informatics & Technology Applications
    Activities: GPA 3.8

  • Harvard University

    2006 – 2015
    Graduate studies (36 credit hours)
    Concentration: Medical genomics, virology and immunology, infectious disease, neurobiology, epidemiology
    Activities: GPA 3.3

  • Harvard University

    2006 – 2008
    General Studies
    Concentration: Neurobiology, epidemiology, infectious disease & environmental sciences

  • Harvard Law School

    2001 – 2001
    Certificates (5)
    Concentration: Program on Negotiation
    Activities: Dealing With Difficult People & Difficult Situations (June 2001) The Program on Negotiation for Senior Executives (April 2001) Dealing with an Angry Public (May 2001) Managing the Difficult Business Conversation (April 2001) Negotiating Labor Agreements (July 2001)

  • University of Pennsylvania's Wharton School of Business

    2000 – 2001
    Fellow
    Concentration: E-commerce

  • California Institute of Technology (Caltech)

    2000 – 2000
    Advanced certificate
    Concentration: Business process re-engineering

  • Massachusetts Institute of Technology (MIT), Sloan School of Management

    2000 – 2000
    Advanced certificates (2)
    Concentration: Finance & technology

  • Columbia University, Graduate School of Business

    2000 – 2000
    Advanced certificate
    Concentration: Mergers & acquisitions

  • CalTech

    2000 – 2000
    Advanced Certificate
    Concentration: Business Process Re-engineering

  • American University

    1990 – 1995
    Bachelor of arts
    Concentration: Liberal Arts & Economics

Eric Luellen's Interests & Activities:

in addition to applying systems and data science, AI and machine learning to challenges in healthcare, fintech, education, and retail, Eric Luellen enjoys hiking, adventure travel, and photography. In 2018, he won an honorable mention for the Neutral Density Photography Award for an aerial landscape of the Greenland ice cap.